Tootfinder

our "don't rank cuomo" chant didn't take but the #mets won. #nyc

#HeatherStephens #JeremyJackson #DonDiamont
Season 8 Episode 22 "White Thunder at Glacier Bay: part 2"

Am Samstag wird er 95 Jahre alt : Clint Eastwood
#Schauspieler #Actor #Senior

Rastlose Legende: Hollywood-Ikone Clint Eastwood wird 95
Er ist Schauspieler, Regisseur, Produzent – und seit Jahrzehnten eine Ausnahmefigur in Hollywood. Zum 95. Geburtstag von Clint Eastwood zeigt sich: Der Mann im Cowboyhut bleibt rastlos, selbst nach einem schmerzlichen Verlust.

Een zelfversterkend effect.
From: @…
https://social.overheid.nl/@knmi/114586081449197034

Throwback to when I upgraded my beaten up purple #GameBoy #Advance case to a new transparent body. I love the orange accents. The screen is a glass lens which gives it a bit more cachet compared to the original plastic one.

This https://arxiv.org/abs/2412.07951 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agents
Recent gains in popularity of AI conversational agents have led to their increased use for improving productivity and supporting well-being. While previous research has aimed to understand the risks associated with interactions with AI conversational agents, these studies often fall short in capturing the lived experiences of individuals. Additionally, psychological risks have often been presented as a sub-category within broader AI-related risks in past taxonomy works, leading to under-represe…

Join Dennis Berger, Marco Petris, and Volker Carlguth to explore 'Intent-Based Clustering.' An approach to overcome some limitations of modern hybrid search systems. Discover how upfront LLM-supported in-depth query understanding can be applied in various steps, including retrieval, clustering, validation, and presentation. Learn about the process of moving from prototype to production for large-scale, high-volume e-commerce searches.

What you see is what you mean; intent based ecommerce search
In today's e-commerce landscape, hybrid search systems represent the market standard, yet they often struggle with highly inspirational queries, lack of precision in semantic recall, and presentation of diversity. Ambiguity in search terms can lead to disorganized results or overshadowed relevant products. This session will demonstrate how an upfront LLM-supported in depth query understanding can increase recall meaningfully without sacrificing precision. We show how LLM-driven query understand…

This https://arxiv.org/abs/2304.13452 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On signed Mordell-Weil groups for abelian varieties
In this short note, we work in the general framework of supersingular abelian varieties defined over $\mathbb{Q}$. Using Coleman maps constructed by Buuyukboduk--Lei, we define some new objects called ``the multi-signed Mordell-Weil groups" for supersingular abelian varieties, provide an explicit structure of the dual of these groups as an Iwasawa module and prove a control theorem. This recovers the case of elliptic curves over $\mathbb{Q}$ non-ordinary at the prime $p$ with $a_p=0$ studied by…

This https://arxiv.org/abs/2505.19312 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

DocMMIR: A Framework for Document Multi-modal Information Retrieval
The rapid advancement of unsupervised representation learning and large-scale pre-trained vision-language models has significantly improved cross-modal retrieval tasks. However, existing multi-modal information retrieval (MMIR) studies lack a comprehensive exploration of document-level retrieval and suffer from the absence of cross-domain datasets at this granularity. To address this limitation, we introduce DocMMIR, a novel multi-modal document retrieval framework designed explicitly to unify …

Spectrotemporal Modulation: Efficient and Interpretable Feature Representation for Classifying Speech, Music, and Environmental Sounds
Andrew Chang, Yike Li, Iran R. Roman, David Poeppel
https://arxiv.org/abs/2505.23509

Spectrotemporal Modulation: Efficient and Interpretable Feature Representation for Classifying Speech, Music, and Environmental Sounds
Audio DNNs have demonstrated impressive performance on various machine listening tasks; however, most of their representations are computationally costly and uninterpretable, leaving room for optimization. Here, we propose a novel approach centered on spectrotemporal modulation (STM) features, a signal processing method that mimics the neurophysiological representation in the human auditory cortex. The classification performance of our STM-based model, without any pretraining, is comparable to …